Marketing data science informs decisions across Uber's global marketing efforts, accelerating both demand and supply growth worldwide. We leverage advanced statistical modeling, machine learning, or data mining techniques in a scalable manner including large scale data processing such as Spark, Hive, and Uber's proprietary machine learning platform, and more.
About the role
We're growing our teams across Global Marketing Data Science and looking for Data Scientists to provide data expertise as we improve the growth, retention, engagement, and brand affinity of the eaters on the Uber platform. In the role, you'll be part of and collaborate with a cross-functional team consisting of strategy, design, development, program, and operation managers.
You possess a passion for improving techniques, processes, tracking, analytical insights, and technology used by marketing to achieve our bold goals. You will help address the complex challenges of experiment design, budget allocation, marketing effectiveness, contact strategy, return on investment, user behavior, and channel effectiveness using state-of-the-art machine learning models.
As a member of marketing data science, you will not only be able to work with data, but also help define the way marketing performance is calibrated and what questions should be asked. You'll play a big part in finding opportunity fields to help the marketing function scale as we develop onboarding, engagement and retention strategies. You will also learn and apply advanced analytics skills like experimental design, statistical modeling, and more.
What you'll do

• Mine data and analytics at the customer level to gain a better understanding of their usage behaviors, including impacts of current marketing strategies.
• Utilize non-individual level measurement methods when applicable, like market-level testing, to help understand the impact of marketing spend and the related return it can drive.
• Use sophisticated modeling techniques such as causal inference to undercover insights related to user behavior.
• Collaborate closely with Applied Sciences to understand the ins and outs of various machine learning models, as well as help, understand their performance and areas of improvement.
• Work closely with the paid and CRM marketing teams and be responsible for campaign pre and post-analysis, cohorting, experiment design, segmentation, KPI measurement, and more.
• Collaborate on cross-functional project planning/prioritization meetings, business partner meetings, data prioritization meetings, etc.
• Choose the accurate metrics for tracking and understanding current and future experiments.
• Implement and analyze A/B or Multivariate Tests to provide measurable insights to the marketing team on the test data.
• Present findings to senior management to drive business and marketing decisions.
• Develop dashboards that provide reliable insights and visualization.
• Use tools such as Google Sheet, Jupyter notebooks, and many internal tools to work efficiently at scale.
• Be a key driver of marketing strategy, by thinking beyond immediate analysis to understand the long-term implications of actions.

Basic qualifications

• M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience as a Data Scientist or equivalent)
• Advanced SQL expertise
• Basic understanding of experimental design (such as A/B experiments) and statistical methods
• Ability and experience in extracting insights from data, and summarizing learnings / takeaways
• Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar)

Preferred qualifications

• Marketing/product data science or consulting experience
• Search Engine Optimization analytics experience
• Advanced experimentation experience including multivariate and causal analysis
• Speed, resourcefulness, and a go-getter attitude
• AdTech experience is a plus
• Experience working on web analytics (behavioral analytics)
• Detailed knowledge of data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
• Solid understanding of source data, its strengths, weaknesses, semantics, and formats; solid knowledge of logical and physical data modeling concepts (relational and dimensional)
• Someone who is willing to contribute new ideas and articulate them to a variety of business partners and not just execute on existing ones